Evaluation of Swedish lake water quality modelling from remote sensing

The main aim of this work was to construct and validate a mathematical water quality model of the Dianchi lake, so that by altering input total phosphate (TP) loads the projected changes in the lake water TP concentrations could be estimated. Historical information had indicated deteriorating lake water quality with increasing TP concentrations. The model was based on a simple annual mass balance, relying on 3 years (wet, average and dry) data with all TP loads quantified, 7 years of lake water quality, and 36 years of flow data. All lake processes were considered within a single variable, R. Planning TP removal at STWs and within fertilizer plants, coupled with interventions to reduce non-point TP loads from all land run-off by 50%, suggested future lake water TP concentrations could be stabilised at about 0.3 mg TP/l, i.e. the estimated limit for producing algal concentrations that would cause major problems in water treatment plants. The TP load reductions envisaged as realistic would only stabilise the lake water quality by about the year 2008; interventions, unfortunately, could not return the lake to its former pristine condition. The accuracy of the predictions was ± 0.1 mg TP/1, so collection of better data was needed.

Download Full-text

A semi-operative approach to lake water quality retrieval from remote sensing data

The Science of The Total Environment ◽

10.1016/s0048-9697(00)00687-2 ◽

2001 ◽

Vol 268 (1-3) ◽

pp. 79-93 ◽

Cited By ~ 91

Author(s):

Jouni Pulliainen ◽

Kari Kallio ◽

Karri Eloheimo ◽

Sampsa Koponen ◽

Henri Servomaa ◽

...

Keyword(s):

Remote Sensing ◽

Water Quality ◽

Lake Water ◽

Remote Sensing Data ◽

Operative Approach ◽

Lake Water Quality ◽

Sensing Data

Download Full-text

Numerical Simulation of Donghu Lake Hydrodynamics and Water Quality Based on Remote Sensing and MIKE 21

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9020094 ◽

2020 ◽

Vol 9 (2) ◽

pp. 94 ◽

Cited By ~ 3

Author(s):

Xiaojuan Li ◽

Mutao Huang ◽

Ronghui Wang

Keyword(s):

Remote Sensing ◽

Numerical Simulation ◽

Water Quality ◽

Lake Water ◽

Quality Data ◽

Lake Water Quality ◽

Water Quality Simulation ◽

Donghu Lake ◽

Mean Square Errors

Numerical simulation is an important method used in studying the evolution mechanisms of lake water quality. At the same time, lake water quality inversion technology using the characteristics of spatial optical continuity data from remote sensing satellites is constantly improving. It is, however, a research hotspot to combine the spatial and temporal advantages of both methods, in order to develop accurate simulation and prediction technology for lake water quality. This paper takes Donghu Lake in Wuhan as its research area. The spatial data from remote sensing and water quality monitoring information was used to construct a multi-source nonlinear regression fitting model (genetic algorithm (GA)-back propagation (BP) model) to invert the water quality of the lake. Based on the meteorological and hydrological data, as well as basic water quality data, a hydrodynamic model was established by using the MIKE21 model to simulate the evolution rules of water quality in Donghu Lake. Combining the advantages of the two, the best inversion results were used to provide a data supplement for optimization of the water quality simulation process, improving the accuracy and quality of the simulation. The statistical results were compared with water quality simulation results based on the data measured. The results show that the water quality simulation of chlorophyll a and nitrate nitrogen mean square errors fell to 17% and 24%, from 19% and 31% respectively, after optimization using remote sensing spatial information. The model precision was thus improved, and this is consistent with the actual pollution situation of Donghu Lake.

Download Full-text